library(tidyverse)
library(sf)
library(tmap)
library(rnaturalearth)
library(rnaturalearthdata)
library(rnaturalearthhires)
weather <- read_csv('sewanee_weather.csv')
## Warning: One or more parsing issues, call `problems()` on your data frame for details,
## e.g.:
## dat <- vroom(...)
## problems(dat)
knitr::opts_chunk$set(echo = TRUE, warning = FALSE, message = FALSE)
head(weather)
## # A tibble: 6 Ă— 38
## STATION NAME LATITUDE LONGITUDE ELEVATION DATE DAPR DAPR_ATTRIBUTES
## <chr> <chr> <dbl> <dbl> <dbl> <date> <dbl> <chr>
## 1 USC004081… SEWA… 35.2 -85.9 588. 2000-06-01 NA <NA>
## 2 USC004081… SEWA… 35.2 -85.9 588. 2000-06-02 NA <NA>
## 3 USC004081… SEWA… 35.2 -85.9 588. 2000-06-03 NA <NA>
## 4 USC004081… SEWA… 35.2 -85.9 588. 2000-06-04 NA <NA>
## 5 USC004081… SEWA… 35.2 -85.9 588. 2000-06-05 NA <NA>
## 6 USC004081… SEWA… 35.2 -85.9 588. 2000-06-06 NA <NA>
## # ℹ 30 more variables: MDPR <dbl>, MDPR_ATTRIBUTES <chr>, PRCP <dbl>,
## # PRCP_ATTRIBUTES <chr>, SNOW <dbl>, SNOW_ATTRIBUTES <chr>, SNWD <dbl>,
## # SNWD_ATTRIBUTES <chr>, TMAX <dbl>, TMAX_ATTRIBUTES <chr>, TMIN <dbl>,
## # TMIN_ATTRIBUTES <chr>, TOBS <dbl>, TOBS_ATTRIBUTES <chr>, WESD <lgl>,
## # WESD_ATTRIBUTES <lgl>, WESF <lgl>, WESF_ATTRIBUTES <lgl>, WT01 <dbl>,
## # WT01_ATTRIBUTES <chr>, WT03 <dbl>, WT03_ATTRIBUTES <chr>, WT04 <dbl>,
## # WT04_ATTRIBUTES <chr>, WT05 <lgl>, WT05_ATTRIBUTES <lgl>, WT06 <dbl>, …
y2000 <- weather %>% filter(year(DATE) <= 2005)
y2005 <- weather %>% filter(year(DATE) > 2005 & year(DATE) <= 2010)
y2010 <- weather %>% filter(year(DATE) > 2010 & year(DATE) <= 2015)
y2015 <- weather %>% filter(year(DATE) > 2015 & year(DATE) <= 2020)
ggplot(data = y2000, aes(x = DATE, y = TMAX)) +
geom_point() +
labs(title = "Temperature Data up to 2005", x = "Date", y = "Max Temperature (TMAX)")
ggplot(data = y2005, aes(x = DATE, y = TMAX)) +
geom_point() +
labs(title = "Temperature Data from 2006 to 2010", x = "Date", y = "Max Temperature (TMAX)")
ggplot(data = y2010, aes(x = DATE, y = TMAX)) +
geom_point() +
labs(title = "Temperature Data from 2011 to 2015", x = "Date", y = "Max Temperature (TMAX)")
ggplot(data = y2015, aes(x = DATE, y = TMAX)) +
geom_point() +
labs(title = "Temperature Data from 2016 to 2020", x = "Date", y = "Max Temperature (TMAX)")
### plots together
y2000 <- weather %>%
filter(year(DATE) <= 2005) %>%
mutate(Period = "2000-2005")
y2015 <- weather %>%
filter(year(DATE) > 2015 & year(DATE) <= 2020) %>%
mutate(Period = "2015-2020")
combined_data <- bind_rows(y2000, y2015)
ggplot(data = combined_data, aes(x = DATE, y = TMAX, color = Period)) +
geom_point(alpha = 0.8) +
labs(title = "Comparison of Temperature Data: 2000-2005 vs 2015-2020",
x = "Date",
y = "Max Temperature (TMAX)")
ggplot(data = y2000, aes(x = DATE, y = TMIN)) +
geom_point() +
labs(title = "Temperature Data up to 2005", x = "Date", y = "Max Temperature (TMIN)")
ggplot(data = y2005, aes(x = DATE, y = TMIN)) +
geom_point() +
labs(title = "Temperature Data from 2006 to 2010", x = "Date", y = "Max Temperature (TMIN)")
ggplot(data = y2010, aes(x = DATE, y = TMIN)) +
geom_point() +
labs(title = "Temperature Data from 2011 to 2015", x = "Date", y = "Max Temperature (TMIN)")
ggplot(data = y2015, aes(x = DATE, y = TMIN)) +
geom_point() +
labs(title = "Temperature Data from 2016 to 2020", x = "Date", y = "Max Temperature (TMIN)")
ggplot(data = combined_data, aes(x = DATE, y = TMIN, color = Period)) +
geom_point(alpha = 0.8) +
labs(title = "Comparison of Temperature Data: 2000-2005 vs 2015-2020",
x = "Date",
y = "Max Temperature (TMIN)")
overall_avg_2000 <- y2000 %>%
summarise(
avg_TMAX = mean(TMAX, na.rm = TRUE),
avg_TMIN = mean(TMIN, na.rm = TRUE)
)
overall_avg_2000
## # A tibble: 1 Ă— 2
## avg_TMAX avg_TMIN
## <dbl> <dbl>
## 1 65.4 48.2
overall_avg_2015 <- y2015 %>%
summarise(
avg_TMAX = mean(TMAX, na.rm = TRUE),
avg_TMIN = mean(TMIN, na.rm = TRUE)
)
overall_avg_2015
## # A tibble: 1 Ă— 2
## avg_TMAX avg_TMIN
## <dbl> <dbl>
## 1 67.7 50.2
tempp <- weather %>%
group_by(year = year(DATE)) %>%
summarise(
avg_TMAX = mean(TMAX, na.rm = TRUE),
avg_TMIN = mean(TMIN, na.rm = TRUE)
)
ggplot() +
geom_line(data = tempp, aes(x = year, y = avg_TMAX, color = "avg_TMAX"), size = 0.8) +
geom_line(data = tempp, aes(x = year, y = avg_TMIN, color = "avg_TMIN"), size = 0.8) +
labs(title = "Yearly Average Max and Min Temperatures",
x = "Year",
y = "Average Temperature",
color = "Temperature Type")
tempp <- tempp %>%
mutate( avgtemp = (avg_TMIN + avg_TMAX) / 2 )
ggplot() +
geom_line(data = tempp, aes(x = year, y = avgtemp), size = 0.8) +
labs(title = "Yearly Average Max and Min Temperatures",
x = "Year",
y = "Average Temperature")
it drops off at the end because the latest date was 7 days ago so the
mean is lower because it’s only been winter same thing for the
start.